Academic integrity as a basis for the policy using artificial intelligence technologies in higher education institutions
DOI:
https://doi.org/10.5281/zenodo.15321735Keywords:
academic integrity, artificial intelligence, student, academic staff, neural network, ChatGPTAbstract
Artificial intelligence (AI) technologies are a modern element of the modernisation of educational and scientific process in higher education institutions. Neural networks allow to improve the learning process of students, helping them to acquire theoretical and practical skills of the speciality they are studying. AI technologies allow academic staff to carry out innovative ongoing monitoring of students' learning, to work more productively on the methodological and scientific component of the educational process. The purpose of the article is to study the policy of using AI neural networks in terms of compliance with the principles of academic integrity to identify and prevent their violations. Methods. To achieve this goal, a comprehensive analysis of the implementation of the modern scientific theory of the use of AI technologies in the educational process of higher education institutions of Ukraine was accomplished. The data on the existing policy practices of Ukrainian higher education institutions and the recommendations of the European Network of Academic Integrity (ENAI) were also taken into account. Results. The peculiarities of legislative consolidation of academic integrity norms in higher education institutions of Ukraine, implementation of the principles of academic integrity in the context of using AI neural networks in their works are determined. As an example, the article analyses the principles of policy and organisation of the student honour code at the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” and offers recommendations for improving the forms of compliance with the principles of academic integrity by participants of the educational and research processes. The types of academic responsibility are considered, the legal and practical consequences of dishonest activity are determined. Conclusions. Artificial intelligence technologies have the potential to improve the educational process and contribute to the efficiency of academic performance. On the other hand, their use requires coordination and is subject to the principles of academic integrity. An effective mechanism is the introduction of new rules and modernisation of the existing ones both at the individual level in terms of educational and research policies of each higher education institution and the national legislative field.
